Monitoring the extraction process of acidic polysaccharides in Poria cocos by near infrared spectroscopy combined with chemometrics

Abstract

In this work, an analytical model based on near infrared spectroscopy is proposed to predict the main active ingredients of Poria cocos (PC) during the extraction process, acidic polysaccharides. In order to improve the prediction quality, various pretreatment methods and variable selection methods were carefully compared and the partial least squares method was used to relate the predicted values to the reference ones. As a result, a robust and optimal model was obtained, where the coefficient of determination, root mean square error and mean absolute error were 0.9618, 4.05% and 3.26% for calibration, and 0.9609, 4.17% and 3.31% for prediction, respectively. The residual prediction deviation reached 5.15. Such satisfying results clearly showed that the present model had very good prediction ability and thus had great potential for monitoring of the extraction process of PC in the pharmaceutical manufacturing.